Explainable AI (XAI) in IoT Decisions

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Question ^*

What are the biggest challenges you anticipate in implementing XAI for your IoT system?

1. (a) Lack of technical expertise

2. (b) Complexity of XAI methods

3. (c) Data privacy concerns

4. (d) Integration with existing systems

5. (e) Computational cost

6. (f) Limited understanding of XAI benefits

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Question ^*

What type of explanations would be most valuable for your IoT decisions?

1. (a) Feature importance rankings

2. (b) Visualizations of decision-making processes

3. (c) Natural language explanations

4. (d) Simulations of "what-if" scenarios

5. (e) Detailed code-level insights

6. (f) Other: __________

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Question ^*

How important is understanding why an IoT device made a particular decision in your application?

1. (a) Not at all important

2. (b) Slightly important

3. (c) Moderately important

4. (d) Very important

5. (e) Extremely important

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Question ^*

Which of these aspects are most critical when using AI for IoT decision-making?

1. (a) Accuracy of predictions

2. (b) Speed of decision-making

3. (c) *Explainability* of the decisions

4. (d) Security of data

5. (e) Cost-effectiveness

6. (f) Scalability

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Question ^*

In which IoT application areas is XAI most needed to improve decision-making?

1. (a) Predictive Maintenance

2. (b) Smart Agriculture

3. (c) Healthcare Monitoring

4. (d) Smart Home Automation

5. (e) Industrial Automation

6. (f) Energy Management

7. (g) Other: __________

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